Nathan Lambert argues that 2026 AI progress is becoming higher-stakes, with model capabilities, work patterns, economics, and real-world risks all escalating. He says open models still lack a true Claude Code and Opus 4.5-style agent moment, and Gemini has no clear competitor to Claude Code or Codex yet. The essay also tracks Mythos, American open-model momentum, frontier-lab competition, and mounting intervention from governments and other power structures.
在 Google I/O 大會前夕的空檔,Latent Space 特別推薦了一篇備受關注的部落格文章。該文深入探討求職者如何準備並進入頂尖 AI 實驗室(如 OpenAI、Anthropic 等)從事核心的「預訓練(Pretraining)」工作。內容涵蓋預訓練工程師所需的關鍵技能、知識儲備與面試準備方向,是志在投身前沿 AI 研發者的必讀指南。